Signals shaping
health AI.
A focused stream of research, industry developments and ideas selected for people building the future of health.
Research and developments, with a clear point of view.
Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement.
Machine learning models effectively classify cervical vertebral maturation stages, achieving up to 77.4% accuracy....
Machine Learning-Based Approach for Identifying Research Gaps: COVID-19 as a Case Study.
A machine learning approach identifies COVID-19 research gaps, highlighting six key topics for future...
Enhancing reginal wall abnormality detection accuracy: Integrating machine learning, optical flow algorithms, and temporal convolutional networks in multi-view echocardiography.
Recent research enhances RWMA detection using machine learning and multi-view echocardiography. Promising results for...
Supporting Trustworthy AI Through Machine Unlearning.
Machine unlearning can enhance trustworthy AI by supporting ethical principles. However, it poses ethical...
Fall risk prediction using temporal gait features and machine learning approaches.
AI enhances fall risk prediction through gait analysis. 🤖🚶♂️ Promising results with 96% accuracy...
Adult co-creators’ emotional and psychological experiences of the co-creation process: a Health CASCADE scoping review protocol.
Exploring adult co-creators' emotional and psychological experiences in health co-creation processes. 🧠🤝 #HealthCASCADE #CoCreation
Comparing Cadence vs. Machine Learning Based Physical Activity Intensity Classifications: Variations in the Associations of Physical Activity With Mortality.
New research compares cadence and machine learning in classifying physical activity intensity and its...
Treatment effect analysis of the Frailty Care Bundle (FCB) in a cohort of patients in acute care settings.
Exploring the Frailty Care Bundle's impact on older patients' mobility using machine learning. 🤖👵...
Analysis of Responses of GPT-4 V to the Japanese National Clinical Engineer Licensing Examination.
GPT-4 V scored 86% on Japan's Clinical Engineer Exam. 📊 Performance varied by subject;...